Each anomaly detection job has one or more detectors. A detector applies an analytical
function to specific fields in your data. For more information about the types
of analysis you can perform, see Function reference.

A job can also contain properties that affect which types of entities or events
are considered anomalous. For example, you can specify whether entities are
analyzed relative to their own previous behavior or relative to other entities
in a population. There are also multiple options for splitting the data into
categories and partitions. Some of these more advanced job configurations
are described in the following section: Configuring machine learning.

In Kibana, there are wizards that help you create specific types of jobs, such
as single metric, multi-metric, and population jobs. A single metric job
is just a job with a single detector and limited job properties. To have access
to all of the job properties in Kibana, you must choose the advanced job wizard.

You can also optionally assign jobs to one or more job groups. You can use
job groups to view the results from multiple jobs more easily and to expedite
administrative tasks by opening or closing multiple jobs at once.